Automatic de-noising and recognition algorithm for drilling fluid pulse signal

被引：0
|
作者：
Hu Y. [1 ]
Huang Y. [1 ]
Li X. [1 ]
机构：
[1] CNPC Engineering Technology R&D Company Ltd., Beijing
来源：
Shiyou Kantan Yu Kaifa/Petroleum Exploration and Development | 2019年 / 46卷 / 02期
关键词：
Automatic de-noising and recognition; Decoding success rate; Drilling fluid; Peak detection; Pulse signal; Signal processing; Synchronous decoding; Wavelet forced de-noising;
D O I：
10.11698/PED.2019.02.18
中图分类号：
学科分类号：
摘要：
Wavelet forced de-noising algorithm is suitable for denoising of unsteady drilling fluid pulse signal, including baseline drift rectification and two-stage de-noising processing of frame synchronization signal and instruction signal. Two-stage de-noising processing can reduce the impact of baseline drift and determine automatic peak detection threshold range for signal recognition by distinguishing different features of frame synchronization pulse and instruction pulse. Rising and falling edge relative protruding threshold is defined for peak detection in signal recognition, which can make full use of the degree of the signal peak change and detect peaks flexibly with rising and falling edge relative protruding threshold combination. A synchronous decoding method was designed to reduce position uncertainty of the frame synchronization pulse and eliminate the accumulative error of time base drift, which determines the first instruction pulse position according to position of the frame synchronization pulse and decodes subsequent instruction pulse by taking current instruction pulse as new bit synchronization pulse. Special tool software was developed to tune algorithm parameters, which has a decoding success rate of about 95% for the universal coded signals. For the special coded signals with check byte, decoding success rate using the automatic threshold adjustment algorithm is as high as 99%. © 2019, The Editorial Board of Petroleum Exploration and Development. All right reserved.
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页码：378 / 384
页数：6
相关论文
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